1. Technical Field
The present invention relates in general to a method and apparatus for automatically recognizing blood cells, and in particular, to a method and apparatus for automatically recognizing blood cell type by using an image processing and a neural network mechanism in a computer system.
2. Description of the Related Art
Normal white blood cells observed in blood are largely divided into neutrophils, lymphocytes, monocytes, basophils, and eosinophils. The occurrence of immature blood cells such as a blast, a normoblast, and an immature granulocyte is indicative of blood diseases. Accordingly, blood cell recognition methods are required to diagnose blood diseases such as leukemia. The recognition of blood cells can be performed manually or automatically. In the manual recognition method, an examiner has to observe blood cells with a microscope, so it requires a lot of time and effort. This method is therefore inappropriate to be utilized in large hospitals.
In counting the white blood cells in a blood sample, two methods have been developed and used for an automatic blood recognizer. The first method, which has been predominantly used to date, employs the combination of cytochemistry, electric impedance (impedance method), and a light scatter principle (optical method). The impedance method is based on the measurement of changes in an electrical current which are produced by a particle, suspended in a conductive liquid, as it passes through an aperture of known dimensions. In the optical method, a suspension of a diluted blood sample passes through a laser light test section where the cells scatter the laser light at different angles, yielding information about the size, internal structure, granularity and surface morphology. However, this method can only either recognize the five kinds of normal white blood cells or classify the cells into three or four separate functions. For instance, U.S. Pat. No. 4,581,223 introduces new staining solutions for an improved cytochemical reaction but only five individual white blood cells are identified by selective use of basic quaternary metachromatic dye staining of blood at a controlled temperature. Immature cells are not recognized. International patent application PCT/US88/00960 describes an electronic counting method but this method also enables recognition of the above five kinds of white blood cells. The patent application, PCT/US85/00840 is directed to a reference control solution for an electronic threshold setting, but only for three separate white blood cell control portions (lymphocytes, mononuclear cells and granulocytes). Other examples are also available. See European Pat. EP 0 424 871 A1 and U.S. Pat. No. 5,045,474. The most well known blood cell counters based on above principles are the so-called Coulter Counter and Cell-Dyn Counter.
The second method is based on a pattern recognition method in which the white blood cells are recognized after their images have been acquired followed by digitized and image-processed in a computer. U.S. Pat. No. 4,338,024 discloses a method of obtaining still images of objects in a flow stream on a CCD camera. Successive results of investigation of this patent were published in Clinical Chemistry (40/9, pp. 1850-1861, 1994). In U.S. Pat. No. 4,175,860, a method and apparatus is disclosed for use in performing automated classification of cells using a set of images, i.e., a high resolution image of primarily the nucleus of a cell and a low resolution image of the total cell. The high-resolution image is processed to obtain information on the texture whereas the low-resolution image is processed to obtain information on the size, density and color of the cytoplasm and the nucleus. In U.S. Pat. No. 5,123,055, a method and apparatus is provided for automatically identifying the five kinds of white blood cells. However, so far, to applicant's knowledge, there has not been a simple and efficient method of differentiating the five kinds of white blood cells and critical immature blood cells. In addition, none of above mentioned references have disclosed a method of recognition which combines both a statistical module and a neural network.